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Abstract
Animal production is responsible for 56–58% of the GHG emissions and limiting meat consumption would strongly contribute to reducing human health risks in Western countries. This study aimed to investigate the nature of protein intake as a discriminating factor for diets’ sustainability. Using data from 29,210 French adults involved in the NutriNet-Santé cohort, we identified clusters according to 23 protein sources. A multicriteria (environmental, economic, nutritional and health) sustainability analysis was then conducted on the identified clusters. The economic analysis focused on both food and protein expenditure structures, using a budget coefficient approach. Relative values of clusters compared to the whole sample were calculated. We identified five clusters: milk-based, meat-based, fast food-based, healthy-fish-based, and healthy-plant-based. We found that the healthy-plant-based and healthy-fish-based clusters were the most sustainable, conciliating the compromise between human health (0.25 and 0.53 respectively for the Health Risk Score) and the protection of the environment (− 62% and − 19% respectively for the pReCiPe indicator). Conversely, the highest environmental impacts (+ 33% for the pReCiPe indicator) and the highest health risk (0.95 for the HRS) were observed for the meat-based cluster, which was associated with the lowest nutritional scores (− 61% for the PNNS-GS2 score). The economic analysis showed that the healthy-plant-based cluster was the one with the highest food budget coefficient (+ 46%), followed by the healthy-fish-based cluster (+ 8%), partly explained by a strong share of organic food in the diet. However, the meat-based cluster spent more of their food budget on their protein intake (+ 13%), while the healthy-plant-based cluster exhibited the lowest expenditure for this intake (− 41%). Our results demonstrate that the nature of protein intake is a discriminating factor in diet sustainability. Also, reducing animal protein consumption would generate co-benefits beyond environmental impacts, by being favorable for health, while reducing the monetary cost associated with protein intake.
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Details
1 Inserm, INRAE, CNAM, Center of Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), Université Sorbonne Paris Nord and Université Paris Cité, Bobigny, France
2 Inserm, INRAE, CNAM, Center of Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), Université Sorbonne Paris Nord and Université Paris Cité, Bobigny, France; ADEME, (Agence de l’Environnement et de la Maîtrise de l’Energie), Angers, France (GRID:grid.13570.30) (ISNI:0000 0000 9705 2501)
3 AgroParisTech, INRAE, UMR PNCA, Université Paris-Saclay, Palaiseau, France (GRID:grid.460789.4) (ISNI:0000 0004 4910 6535)
4 Inserm, INRAE, CNAM, Center of Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), Université Sorbonne Paris Nord and Université Paris Cité, Bobigny, France (GRID:grid.460789.4)
5 Inserm, INRAE, C2VN, Aix Marseille Université, Marseille, France (GRID:grid.457381.c) (ISNI:0000 0004 0638 6194)
6 Solagro, Toulouse Cedex 3, France (GRID:grid.437812.b)
7 Inserm, INRAE, CNAM, Center of Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), Université Sorbonne Paris Nord and Université Paris Cité, Bobigny, France (GRID:grid.437812.b)